Data Engineer

Data Engineer Role Summary We are looking for a Data Engineer with 1–3 years of experience to design, build, and maintain data pipelines that support analytics and business reporting. The ideal candidate will have hands-on experience with data processing, SQL, and cloud-based data platforms and be eager to grow in large-scale data engineering and analytics systems. Key Responsibilities Build and maintain ETL / ELT data pipelines from multiple data sources. Develop and optimize SQL queries for data transformation and reporting. Work with structured and semi-structured data (CSV, JSON, Parquet). Assist in designing data models for analytics and reporting use cases. Perform data validation, quality checks, and troubleshooting. Collaborate with data analysts, BI developers, and backend teams. Support batch and basic real-time data processing workflows. Document data pipelines and follow data engineering best practices. Required Skills 1–3 years of hands-on experience in Data Engineering or related roles . Strong knowledge of SQL (joins, subqueries, window functions). Experience with ETL / ELT concepts and data pipelines. Programming experience in Python (preferred) or Java/Scala (basic). Exposure to cloud platforms (AWS / Azure / GCP). Experience with data warehouses or big-data platforms such as: Snowflake, Redshift, BigQuery, Azure Synapse, Databricks (any one). Good to Have Experience with Apache Spark / PySpark . Exposure to orchestration tools (Airflow, Azure Data Factory). Understanding of data warehousing concepts (fact & dimension tables). Experience with version control tools (Git). Familiarity with basic DevOps practices and CI/CD.